A repository for learning LangChain🦜🔗 by building a generative ai application.
This is a web application crawling Linkedin & Twitter data about a person and customizes an ice breaker with them.
To run this project, you will need to add the following environment variables to your .env file
OPENAI_API_KEY
SCRAPIN_API_KEY
TAVILY_API_KEY
TWITTER_API_KEY
TWITTER_API_SECRET
TWITTER_ACCESS_TOKEN
TWITTER_ACCESS_SECRET
LANGCHAIN_TRACING_V2
LANGCHAIN_API_KEY
LANGCHAIN_PROJECT
# Optional
To run this project, you will need to add the following environment variables to your .env file:
Note: This project uses paid API services:
- Scrapin.io for LinkedIn data scraping (20% discount available through this link, includes 20 free credits to start)
- Twitter API (paid) for accessing Twitter data
Important Note: If you enable tracing by setting
LANGCHAIN_TRACING_V2=true
, you must have a valid LangSmith API key set inLANGCHAIN_API_KEY
. Without a valid API key, the application will throw an error. If you don't need tracing, simply remove or comment out these environment variables.
Clone the project
git clone https://github.com/emarco177/ice_breaker.git
Go to the project directory
cd ice_breaker
Install dependencies
pipenv install
Start the flask server
pipenv run app.py
To run tests, run the following command
pipenv run pytest .